As traditional two-parameter constant false alarm rate （CFAR） target detec-tion algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images ...As traditional two-parameter constant false alarm rate （CFAR） target detec-tion algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test （GLRT） is used to deduce the detectors. The performance of the distribution-based CFAR （DBCFAR） detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive.展开更多
信号检测是激光多普勒测速(LDV)系统实现高精度的关键技术,针对LDV中微弱多普勒信号的检测,本文从噪声在频域中的统计特性出发,对多普勒信号进行带阻滤波,结合雷达的恒虚警(CFAR)检测技术,设计了基于频域的单元平方和自适应阈值检测算...信号检测是激光多普勒测速(LDV)系统实现高精度的关键技术,针对LDV中微弱多普勒信号的检测,本文从噪声在频域中的统计特性出发,对多普勒信号进行带阻滤波,结合雷达的恒虚警(CFAR)检测技术,设计了基于频域的单元平方和自适应阈值检测算法以解决在低信噪比(SNR)的环境中LDV的信号检测问题,提高LDV的信号探测能力,同时降低其虚警概率。仿真与实验的结果表明:该算法与固定阈值相比可以在SNR为-12 d B时实现信号的完全检测,保持低虚警概率,运算简单,工程适用性强。展开更多
现代雷达采用宽带线性调频、相位编码等低截获概率(low probability of interception,LPI)波形,发射功率较低,到达侦察接收机的辐射源信号信噪比较低,给被动侦察带来了巨大的挑战。现有的被动检测方法在检测该类信号时,存在一定的局限性...现代雷达采用宽带线性调频、相位编码等低截获概率(low probability of interception,LPI)波形,发射功率较低,到达侦察接收机的辐射源信号信噪比较低,给被动侦察带来了巨大的挑战。现有的被动检测方法在检测该类信号时,存在一定的局限性,比如算法复杂度高、计算量大和实时性较差等。针对上述问题,提出了一种辐射源信号检测方法。在数字信道化预处理的基础上,设计了适合在工程实现的并行流水线结构,基于顺序统计滤波和二元积累完成检测,提高了检测速度,能够实现对低信噪比信号的恒虚警(constant false alarm rate,CFAR)检测。仿真试验证明了所提方法的有效性和正确性,为辐射源信号检测提供了有力的理论支撑。展开更多
针对复杂非均匀水下环境中目标检测问题,提出了一种基于背景统计特性的鲁棒声呐恒虚警(Background Statistical Characteristics based Robust Sonar Target Constant False Alarm Ratio,BSCR-CFAR)检测算法。该算法将自动删除平均级检...针对复杂非均匀水下环境中目标检测问题,提出了一种基于背景统计特性的鲁棒声呐恒虚警(Background Statistical Characteristics based Robust Sonar Target Constant False Alarm Ratio,BSCR-CFAR)检测算法。该算法将自动删除平均级检测(Automatic Censored Mean Level Detection,ACMLD)和排序统计恒虚警(Order Statistic CFAR,OS-CFAR)检测算法引入可变指数恒虚警(Variability Index CFAR,VI-CFAR)检测算法中,并通过评估背景特性,自适应选择更匹配的CFAR检测方法。仿真和声呐实测数据分析结果表明,相比较单元平均恒虚警(Cell Average CFAR,CA-CFAR)、单元平均选大恒虚警(Greatest of CFAR,GO-CFAR)、单元平均选小恒虚警(Smallest of CFAR,SO-CFAR)和OS-CFAR、VI-CFAR等检测算法,该算法在混响边缘、混响区、单/多强离散干扰等典型非均匀背景下的恒虚警检测保持了良好的鲁棒性。展开更多
文摘As traditional two-parameter constant false alarm rate （CFAR） target detec-tion algorithms in SAR images ignore target distribution, their performances are not the best or near best. As the resolution of SAR images increases, small targets present more pixels in SAR images. So the target distribution is of much significance. Distribution-based CFAR detection algorithm is presented. We unite the pixels around the test cell, and estimate the distribution of test cell by them. Generalized Likelihood Ratio Test （GLRT） is used to deduce the detectors. The performance of the distribution-based CFAR （DBCFAR） detectors is analyzed theoretically. False alarms of DBCFAR detection are fewer than those of CFAR at the same detection rate. Finally experiments are done and the results show the performance of DBCFAR is out of conventional CFAR. False alarms of DBCFAR detection are concentrated while those of CFAR detection are dispersive.
文摘信号检测是激光多普勒测速(LDV)系统实现高精度的关键技术,针对LDV中微弱多普勒信号的检测,本文从噪声在频域中的统计特性出发,对多普勒信号进行带阻滤波,结合雷达的恒虚警(CFAR)检测技术,设计了基于频域的单元平方和自适应阈值检测算法以解决在低信噪比(SNR)的环境中LDV的信号检测问题,提高LDV的信号探测能力,同时降低其虚警概率。仿真与实验的结果表明:该算法与固定阈值相比可以在SNR为-12 d B时实现信号的完全检测,保持低虚警概率,运算简单,工程适用性强。
文摘现代雷达采用宽带线性调频、相位编码等低截获概率(low probability of interception,LPI)波形,发射功率较低,到达侦察接收机的辐射源信号信噪比较低,给被动侦察带来了巨大的挑战。现有的被动检测方法在检测该类信号时,存在一定的局限性,比如算法复杂度高、计算量大和实时性较差等。针对上述问题,提出了一种辐射源信号检测方法。在数字信道化预处理的基础上,设计了适合在工程实现的并行流水线结构,基于顺序统计滤波和二元积累完成检测,提高了检测速度,能够实现对低信噪比信号的恒虚警(constant false alarm rate,CFAR)检测。仿真试验证明了所提方法的有效性和正确性,为辐射源信号检测提供了有力的理论支撑。
文摘针对复杂非均匀水下环境中目标检测问题,提出了一种基于背景统计特性的鲁棒声呐恒虚警(Background Statistical Characteristics based Robust Sonar Target Constant False Alarm Ratio,BSCR-CFAR)检测算法。该算法将自动删除平均级检测(Automatic Censored Mean Level Detection,ACMLD)和排序统计恒虚警(Order Statistic CFAR,OS-CFAR)检测算法引入可变指数恒虚警(Variability Index CFAR,VI-CFAR)检测算法中,并通过评估背景特性,自适应选择更匹配的CFAR检测方法。仿真和声呐实测数据分析结果表明,相比较单元平均恒虚警(Cell Average CFAR,CA-CFAR)、单元平均选大恒虚警(Greatest of CFAR,GO-CFAR)、单元平均选小恒虚警(Smallest of CFAR,SO-CFAR)和OS-CFAR、VI-CFAR等检测算法,该算法在混响边缘、混响区、单/多强离散干扰等典型非均匀背景下的恒虚警检测保持了良好的鲁棒性。
